Ali H. Sayed

Test-Time Collective Classification over Multi-Agent Networks

Test-Time Collaborative Classification over Multi-Agent Networks

This work develops a theoretical and experimental study of this independent training and cooperative inference paradigm, and establishes classification error guarantees under sufficient, finite-round, and finite-precision communication, together with PAC-style generalization bounds.

Decentralized Primal-Dual Learning Over Directed Graphs

Distributed adaptation and learning over directed, unbalanced graphs poses unique challenges due to asymmetric communication and heterogeneous data across nodes. In this work, we introduce a novel class of first-order primal–dual stochastic gradient algorithms for such graphs. Our flagship algorithm, called primal-dual...